STATISTICAL TECHNIQUES-ACCESS ONLY
STATISTICAL TECHNIQUES-ACCESS ONLY
16th Edition
ISBN: 9780077639648
Author: Lind
Publisher: MCG
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Chapter 18, Problem 30CE

Sales of roof material, by quarter, for 2007 through 2013, by Carolina Home Construction Inc. are shown below (in $000).

Chapter 18, Problem 30CE, Sales of roof material, by quarter, for 2007 through 2013, by Carolina Home Construction Inc. are

  1. a. Determine the typical seasonal patterns for sales using the ratio-to-moving-average method.
  2. b. Deseasonalize the data and determine the trend equation.
  3. c. Project sales for 2014 using the trend equation and seasonally adjust these values to find the predicted sales for each quarter.

a.

Expert Solution
Check Mark
To determine

Obtain the typical seasonal patterns for sales using the ratio-to-moving-average method.

Answer to Problem 30CE

The typical seasonal patterns for sales are 1.191168, 1.121778, 0.435094, and 1.251959.

Explanation of Solution

Four-year moving average:

Four-year moving average=sum of the four concequent Sales4

Centered moving average:

Centered moving average=sum of the two concequent moving averages2

Specific seasonal index:

Specific seasonal index=SalesCentered moving average

Consider the following calculations:

YearQuarterVisitors

Four-quarter

moving average

Centered

Moving average

Specific seasonal
20071210
2180
360174.50.34384
4246174179.51.370474
20081214175186.751.145917
2216184187.51.152
382189.5189.50.432718
4230185.51951.179487
20091246193.5197.6251.244782
2228196.52051.112195
391198.75212.750.427732
4280211.252171.290323
20101258214.25222.51.159551
2250219.75227.51.098901
3113225.25232.3750.486283
4298229.75237.1251.256721
20111279235239.6251.164319
2267239.25240.751.109034
3116240244.3750.47468
4304241.5250.1251.215392
20121302247.25252.751.194857
2290253253.251.145114
3114252.5256.3750.444661
4310254258.8751.197489
20131321258.75259.751.235804
2291259261.751.111748
3120260.5
4320263

The quarterly indexes are as follows:

IIIIIIIV
20070.343841.370474
20081.1459171.1520.4327181.179487
20091.2447821.1121950.4277321.290323
20101.1595511.0989010.4862831.256721
20111.1643191.1090340.474681.215392
20121.1948571.1451140.4446611.197489
20131.2358041.111748
Mean1.1908711.1214990.4349861.251648

Typical seasonal index:

Seasonal Index=Mean of the quarter×Correction Factor

Here, Correction Factor=4Sum of the means of the quarters.

Therefore, the following is obtained:

Correction Factor=41.190871+1.121499+0.434986+1.251648=43.999003=1.000249

The seasonal indexes are given below:

IIIIIIIV
20070.343841.370474
20081.1459171.1520.4327181.179487
20091.2447821.1121950.4277321.290323
20101.1595511.0989010.4862831.256721
20111.1643191.1090340.474681.215392
20121.1948571.1451140.4446611.197489
20131.2358041.111748
Mean1.1908711.1214990.4349861.251648
Typical Seasonal Index1.1911681.1217780.4350941.251959

b.

Expert Solution
Check Mark
To determine

Compute the trend equation.

Answer to Problem 30CE

The trend equation is Y^=163.57978+4.13473t.

Explanation of Solution

Deseasonalization:

Deseasonalization=Original salesTypical Index values

SalesTypical seasonal indexDeseasonalized Sales
2101.191168176.29755
1801.121778160.4595562
600.435094137.9012351
2461.251959196.4920576
2141.191168179.6555985
2161.121778192.5514674
820.435094188.4650214
2301.251959183.7120864
2461.191168206.5199871
2281.121778203.2487711
910.435094209.1502066
2801.251959223.6494965
2581.191168216.5941328
2501.121778222.8604947
1130.435094259.7139928
2981.251959238.0269641
2791.191168234.2238878
2671.121778238.0150083
1160.435094266.6090546
3041.251959242.8194534
3021.191168253.5326671
2901.121778258.5181738
1140.435094262.0123468
3101.251959247.6119426
3211.191168269.4833978
2911.121778259.4096158
1200.435094275.8024703
3201.251959255.5994246

Assign t value as 1 for the first quarter of 2007, 2 for the second quarter of 2008, and so on.

Step-by-step procedure to obtain the regression using the Excel:

  • Enter the data for Sales and t in Excel sheet.
  • Go to Data Menu.
  • Click on Data Analysis.
  • Select Regression and click on OK.
  • Select the column of Deseasonalized Sales under Input Y Range.
  • Select the column of t under Input X Range.
  • Click on OK.

Output for the regression obtained using the Excel is as follows:

STATISTICAL TECHNIQUES-ACCESS ONLY, Chapter 18, Problem 30CE

From the Excel output, the regression equation is Y^=163.57978+4.13473t.

c.

Expert Solution
Check Mark
To determine

Predict the sales for the four quarters of 2014 using the trend equation.

Find the seasonally adjusted values.

Answer to Problem 30CE

The sales for the four quarters for 2014 are 283.487, 287.6217, 291.7564, and 295.8911.

The seasonally adjusted values are 337.6806, 322.6477, 126.9415, and 370.4435.

Explanation of Solution

From the output, the regression equation is Y^=163.57978+4.13473t.

The t value for the first quarter of 2014 is 29.

Y^=163.57978+4.13473t=163.57978+(4.13473×29)=283.487

The t value for the second quarter of 2014 is 30.

Y^=163.57978+4.13473t=163.57978+(4.13473×30)=287.6217

The t value for the third quarter of 2014 is 31.

Y^=163.57978+4.13473t=163.57978+(4.13473×31)=291.7564

The t value for the fourth quarter of 2014 is 32.

Y^=163.57978+4.13473t=163.57978+(4.13473×32)=295.8911

Seasonally adjusted forecast:

Estimated VisitorsSeasonal IndexForecast=Estimated Visitors×Seasonal Index
283.4871.191168337.6806
287.62171.121778322.6477
291.75640.435094126.9415
295.89111.251959370.4435

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Chapter 18 Solutions

STATISTICAL TECHNIQUES-ACCESS ONLY

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